Insurance Fraud Claimns Report

Dataset statistics

Number of variables	31
Number of observations	1000
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	242.3 KiB
Average record size in memory	248.1 B

Variable types

Numeric	13
Categorical	17
Boolean	1

Alerts

`months_as_customer` is highly overall correlated with `age`	High correlation
`age` is highly overall correlated with `months_as_customer`	High correlation
`total_claim_amount` is highly overall correlated with `incident_type` and 6 other fields	High correlation
`injury_claim` is highly overall correlated with `incident_type` and 6 other fields	High correlation
`property_claim` is highly overall correlated with `incident_type` and 6 other fields	High correlation
`vehicle_claim` is highly overall correlated with `incident_type` and 6 other fields	High correlation
`incident_type` is highly overall correlated with `collision_type` and 7 other fields	High correlation
`collision_type` is highly overall correlated with `incident_type` and 7 other fields	High correlation
`incident_severity` is highly overall correlated with `incident_type` and 6 other fields	High correlation
`number_of_vehicles_involved` is highly overall correlated with `incident_type` and 1 other fields	High correlation
`fraud_reported` is highly overall correlated with `incident_severity`	High correlation
`authorities_contacted` is highly overall correlated with `incident_type` and 5 other fields	High correlation
`umbrella_limit` has 798 (79.8%) zeros	Zeros
`capital-gains` has 508 (50.8%) zeros	Zeros
`capital-loss` has 475 (47.5%) zeros	Zeros
`incident_hour_of_the_day` has 52 (5.2%) zeros	Zeros
`injury_claim` has 25 (2.5%) zeros	Zeros
`property_claim` has 19 (1.9%) zeros	Zeros

Reproduction

Analysis started	2023-10-31 07:57:47.956998
Analysis finished	2023-10-31 07:58:25.402867
Duration	37.45 seconds
Software version	pandas-profiling vdev
Download configuration	config.json

months_as_customer
Real number (ℝ)

Distinct	391
Distinct (%)	39.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	203.954

Minimum	0
Maximum	479
Zeros	1
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	28.9
Q1	115.75
median	199.5
Q3	276.25
95-th percentile	429.05
Maximum	479
Range	479
Interquartile range (IQR)	160.5

Descriptive statistics

Standard deviation	115.11317
Coefficient of variation (CV)	0.56440754
Kurtosis	-0.48542807
Mean	203.954
Median Absolute Deviation (MAD)	80.5
Skewness	0.36217685
Sum	203954
Variance	13251.043
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
194	8	0.8%
128	7	0.7%
254	7	0.7%
140	7	0.7%
210	7	0.7%
230	7	0.7%
285	7	0.7%
101	7	0.7%
239	6	0.6%
126	6	0.6%
Other values (381)	931	93.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	0.1%
1	3	0.3%
2	2	0.2%
3	2	0.2%
4	3	0.3%
5	2	0.2%
6	1	0.1%
7	1	0.1%
8	3	0.3%
9	2	0.2%

Value	Count	Frequency (%)
479	2	0.2%
478	2	0.2%
476	1	0.1%
475	2	0.2%
473	1	0.1%
472	1	0.1%
468	1	0.1%
467	1	0.1%
465	1	0.1%
464	1	0.1%

age
Real number (ℝ)

Distinct	46
Distinct (%)	4.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38.948

Minimum	19
Maximum	64
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	19
5-th percentile	26
Q1	32
median	38
Q3	44
95-th percentile	57
Maximum	64
Range	45
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	9.1402867
Coefficient of variation (CV)	0.23467923
Kurtosis	-0.26025502
Mean	38.948
Median Absolute Deviation (MAD)	6
Skewness	0.47898805
Sum	38948
Variance	83.544841
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
43	49	4.9%
39	48	4.8%
41	45	4.5%
34	44	4.4%
38	42	4.2%
30	42	4.2%
31	42	4.2%
37	41	4.1%
33	39	3.9%
40	38	3.8%
Other values (36)	570	57.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
19	1	0.1%
20	1	0.1%
21	6	0.6%
22	1	0.1%
23	7	0.7%
24	10	1.0%
25	14	1.4%
26	26	2.6%
27	24	2.4%
28	30	3.0%

Value	Count	Frequency (%)
64	2	0.2%
63	2	0.2%
62	4	0.4%
61	10	1.0%
60	9	0.9%
59	5	0.5%
58	8	0.8%
57	16	1.6%
56	8	0.8%
55	14	1.4%

policy_state
Categorical

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

OH	352
IL	338
IN	310

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	2000
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	OH
2nd row	IN
3rd row	OH
4th row	IL
5th row	IL

Common Values

Value	Count	Frequency (%)
OH	352	35.2%
IL	338	33.8%
IN	310	31.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
oh	352	35.2%
il	338	33.8%
in	310	31.0%

Most occurring characters

Value	Count	Frequency (%)
I	648	32.4%
O	352	17.6%
H	352	17.6%
L	338	16.9%
N	310	15.5%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	2000	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	648	32.4%
O	352	17.6%
H	352	17.6%
L	338	16.9%
N	310	15.5%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2000	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
I	648	32.4%
O	352	17.6%
H	352	17.6%
L	338	16.9%
N	310	15.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
I	648	32.4%
O	352	17.6%
H	352	17.6%
L	338	16.9%
N	310	15.5%

policy_deductable
Categorical

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

1000	351
500	342
2000	307

Length

Max length	4
Median length	4
Mean length	3.658
Min length	3

Characters and Unicode

Total characters	3658
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1000
2nd row	2000
3rd row	2000
4th row	2000
5th row	1000

Common Values

Value	Count	Frequency (%)
1000	351	35.1%
500	342	34.2%
2000	307	30.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1000	351	35.1%
500	342	34.2%
2000	307	30.7%

Most occurring characters

Value	Count	Frequency (%)
0	2658	72.7%
1	351	9.6%
5	342	9.3%
2	307	8.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3658	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	2658	72.7%
1	351	9.6%
5	342	9.3%
2	307	8.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	3658	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	2658	72.7%
1	351	9.6%
5	342	9.3%
2	307	8.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3658	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	2658	72.7%
1	351	9.6%
5	342	9.3%
2	307	8.4%

policy_annual_premium
Real number (ℝ)

Distinct	991
Distinct (%)	99.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1256.4061

Minimum	433.33
Maximum	2047.59
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	433.33
5-th percentile	855.112
Q1	1089.6075
median	1257.2
Q3	1415.695
95-th percentile	1653.4435
Maximum	2047.59
Range	1614.26
Interquartile range (IQR)	326.0875

Descriptive statistics

Standard deviation	244.16739
Coefficient of variation (CV)	0.19433795
Kurtosis	0.07388944
Mean	1256.4061
Median Absolute Deviation (MAD)	164.26
Skewness	0.0044019945
Sum	1256406.1
Variance	59617.717
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1558.29	2	0.2%
1215.36	2	0.2%
1362.87	2	0.2%
1073.83	2	0.2%
1389.13	2	0.2%
1074.07	2	0.2%
1374.22	2	0.2%
1524.45	2	0.2%
1281.25	2	0.2%
1230.69	1	0.1%
Other values (981)	981	98.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
433.33	1	0.1%
484.67	1	0.1%
538.17	1	0.1%
566.11	1	0.1%
617.11	1	0.1%
625.08	1	0.1%
653.66	1	0.1%
664.86	1	0.1%
671.01	1	0.1%
671.92	1	0.1%

Value	Count	Frequency (%)
2047.59	1	0.1%
1969.63	1	0.1%
1935.85	1	0.1%
1927.87	1	0.1%
1922.84	1	0.1%
1896.91	1	0.1%
1878.44	1	0.1%
1865.83	1	0.1%
1863.04	1	0.1%
1861.43	1	0.1%

umbrella_limit
Real number (ℝ)

Distinct	11
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1101000

Minimum	-1000000
Maximum	10000000
Zeros	798
Zeros (%)	79.8%
Negative	1
Negative (%)	0.1%
Memory size	7.9 KiB

Quantile statistics

Minimum	-1000000
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	6000000
Maximum	10000000
Range	11000000
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2297406.6
Coefficient of variation (CV)	2.0866545
Kurtosis	1.7920773
Mean	1101000
Median Absolute Deviation (MAD)	0
Skewness	1.8067122
Sum	1.101 × 10⁹
Variance	5.2780771 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	798	79.8%
6000000	57	5.7%
5000000	46	4.6%
4000000	39	3.9%
7000000	29	2.9%
3000000	12	1.2%
8000000	8	0.8%
9000000	5	0.5%
2000000	3	0.3%
10000000	2	0.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-1000000	1	0.1%
0	798	79.8%
2000000	3	0.3%
3000000	12	1.2%
4000000	39	3.9%
5000000	46	4.6%
6000000	57	5.7%
7000000	29	2.9%
8000000	8	0.8%
9000000	5	0.5%

Value	Count	Frequency (%)
10000000	2	0.2%
9000000	5	0.5%
8000000	8	0.8%
7000000	29	2.9%
6000000	57	5.7%
5000000	46	4.6%
4000000	39	3.9%
3000000	12	1.2%
2000000	3	0.3%
0	798	79.8%

insured_zip
Real number (ℝ)

Distinct	995
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	501214.49

Minimum	430104
Maximum	620962
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	430104
5-th percentile	433273.75
Q1	448404.5
median	466445.5
Q3	603251
95-th percentile	617463.35
Maximum	620962
Range	190858
Interquartile range (IQR)	154846.5

Descriptive statistics

Standard deviation	71701.611
Coefficient of variation (CV)	0.14305574
Kurtosis	-1.1907111
Mean	501214.49
Median Absolute Deviation (MAD)	21841
Skewness	0.81655393
Sum	5.0121449 × 10⁸
Variance	5.141121 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
477695	2	0.2%
469429	2	0.2%
446895	2	0.2%
431202	2	0.2%
456602	2	0.2%
466132	1	0.1%
452218	1	0.1%
608982	1	0.1%
459630	1	0.1%
453193	1	0.1%
Other values (985)	985	98.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
430104	1	0.1%
430141	1	0.1%
430232	1	0.1%
430380	1	0.1%
430567	1	0.1%
430621	1	0.1%
430632	1	0.1%
430665	1	0.1%
430714	1	0.1%
430832	1	0.1%

Value	Count	Frequency (%)
620962	1	0.1%
620869	1	0.1%
620819	1	0.1%
620757	1	0.1%
620737	1	0.1%
620507	1	0.1%
620493	1	0.1%
620473	1	0.1%
620358	1	0.1%
620207	1	0.1%

insured_sex
Categorical

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

FEMALE	537
MALE	463

Length

Max length	6
Median length	6
Mean length	5.074
Min length	4

Characters and Unicode

Total characters	5074
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	MALE
2nd row	MALE
3rd row	FEMALE
4th row	FEMALE
5th row	MALE

Common Values

Value	Count	Frequency (%)
FEMALE	537	53.7%
MALE	463	46.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
female	537	53.7%
male	463	46.3%

Most occurring characters

Value	Count	Frequency (%)
E	1537	30.3%
M	1000	19.7%
A	1000	19.7%
L	1000	19.7%
F	537	10.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	5074	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
E	1537	30.3%
M	1000	19.7%
A	1000	19.7%
L	1000	19.7%
F	537	10.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5074	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
E	1537	30.3%
M	1000	19.7%
A	1000	19.7%
L	1000	19.7%
F	537	10.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5074	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
E	1537	30.3%
M	1000	19.7%
A	1000	19.7%
L	1000	19.7%
F	537	10.6%

insured_education_level
Categorical

Distinct	7
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

JD	161
High School	160
Associate	145
MD	144
Masters	143
Other values (2)	247

Length

Max length	11
Median length	9
Mean length	5.905
Min length	2

Characters and Unicode

Total characters	5905
Distinct characters	20
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	MD
2nd row	MD
3rd row	PhD
4th row	PhD
5th row	Associate

Common Values

Value	Count	Frequency (%)
JD	161	16.1%
High School	160	16.0%
Associate	145	14.5%
MD	144	14.4%
Masters	143	14.3%
PhD	125	12.5%
College	122	12.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
jd	161	13.9%
high	160	13.8%
school	160	13.8%
associate	145	12.5%
md	144	12.4%
masters	143	12.3%
phd	125	10.8%
college	122	10.5%

Most occurring characters

Value	Count	Frequency (%)
o	587	9.9%
s	576	9.8%
e	532	9.0%
h	445	7.5%
D	430	7.3%
l	404	6.8%
i	305	5.2%
c	305	5.2%
t	288	4.9%
a	288	4.9%
Other values (10)	1745	29.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4155	70.4%
Uppercase Letter	1590	26.9%
Space Separator	160	2.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	587	14.1%
s	576	13.9%
e	532	12.8%
h	445	10.7%
l	404	9.7%
i	305	7.3%
c	305	7.3%
t	288	6.9%
a	288	6.9%
g	282	6.8%

Uppercase Letter

Value	Count	Frequency (%)
D	430	27.0%
M	287	18.1%
J	161	10.1%
S	160	10.1%
H	160	10.1%
A	145	9.1%
P	125	7.9%
C	122	7.7%

Space Separator

Value	Count	Frequency (%)
	160	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5745	97.3%
Common	160	2.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	587	10.2%
s	576	10.0%
e	532	9.3%
h	445	7.7%
D	430	7.5%
l	404	7.0%
i	305	5.3%
c	305	5.3%
t	288	5.0%
a	288	5.0%
Other values (9)	1585	27.6%

Common

Value	Count	Frequency (%)
	160	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5905	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	587	9.9%
s	576	9.8%
e	532	9.0%
h	445	7.5%
D	430	7.3%
l	404	6.8%
i	305	5.2%
c	305	5.2%
t	288	4.9%
a	288	4.9%
Other values (10)	1745	29.6%

insured_occupation
Categorical

Distinct	14
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

machine-op-inspct	93
prof-specialty	85
tech-support	78
sales	76
exec-managerial	76
Other values (9)	592

Length

Max length	17
Median length	16
Mean length	13.521
Min length	5

Characters and Unicode

Total characters	13521
Distinct characters	21
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	craft-repair
2nd row	machine-op-inspct
3rd row	sales
4th row	armed-forces
5th row	sales

Common Values

Value	Count	Frequency (%)
machine-op-inspct	93	9.3%
prof-specialty	85	8.5%
tech-support	78	7.8%
sales	76	7.6%
exec-managerial	76	7.6%
craft-repair	74	7.4%
transport-moving	72	7.2%
other-service	71	7.1%
priv-house-serv	71	7.1%
armed-forces	69	6.9%
Other values (4)	235	23.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
machine-op-inspct	93	9.3%
prof-specialty	85	8.5%
tech-support	78	7.8%
sales	76	7.6%
exec-managerial	76	7.6%
craft-repair	74	7.4%
transport-moving	72	7.2%
other-service	71	7.1%
priv-house-serv	71	7.1%
armed-forces	69	6.9%
Other values (4)	235	23.5%

Most occurring characters

Value	Count	Frequency (%)
e	1543	11.4%
r	1379	10.2%
-	1088	8.0%
a	1062	7.9%
s	986	7.3%
i	922	6.8%
c	886	6.6%
p	792	5.9%
t	749	5.5%
o	674	5.0%
Other values (11)	3440	25.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12433	92.0%
Dash Punctuation	1088	8.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1543	12.4%
r	1379	11.1%
a	1062	8.5%
s	986	7.9%
i	922	7.4%
c	886	7.1%
p	792	6.4%
t	749	6.0%
o	674	5.4%
n	620	5.0%
Other values (10)	2820	22.7%

Dash Punctuation

Value	Count	Frequency (%)
-	1088	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12433	92.0%
Common	1088	8.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1543	12.4%
r	1379	11.1%
a	1062	8.5%
s	986	7.9%
i	922	7.4%
c	886	7.1%
p	792	6.4%
t	749	6.0%
o	674	5.4%
n	620	5.0%
Other values (10)	2820	22.7%

Common

Value	Count	Frequency (%)
-	1088	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13521	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1543	11.4%
r	1379	10.2%
-	1088	8.0%
a	1062	7.9%
s	986	7.3%
i	922	6.8%
c	886	6.6%
p	792	5.9%
t	749	5.5%
o	674	5.0%
Other values (11)	3440	25.4%

insured_relationship
Categorical

Distinct	6
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

own-child	183
other-relative	177
not-in-family	174
husband	170
wife	155

Length

Max length	14
Median length	13
Mean length	9.466
Min length	4

Characters and Unicode

Total characters	9466
Distinct characters	20
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	husband
2nd row	other-relative
3rd row	own-child
4th row	unmarried
5th row	unmarried

Common Values

Value	Count	Frequency (%)
own-child	183	18.3%
other-relative	177	17.7%
not-in-family	174	17.4%
husband	170	17.0%
wife	155	15.5%
unmarried	141	14.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
own-child	183	18.3%
other-relative	177	17.7%
not-in-family	174	17.4%
husband	170	17.0%
wife	155	15.5%
unmarried	141	14.1%

Most occurring characters

Value	Count	Frequency (%)
i	1004	10.6%
n	842	8.9%
e	827	8.7%
-	708	7.5%
a	662	7.0%
r	636	6.7%
l	534	5.6%
o	534	5.6%
h	530	5.6%
t	528	5.6%
Other values (10)	2661	28.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8758	92.5%
Dash Punctuation	708	7.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	1004	11.5%
n	842	9.6%
e	827	9.4%
a	662	7.6%
r	636	7.3%
l	534	6.1%
o	534	6.1%
h	530	6.1%
t	528	6.0%
d	494	5.6%
Other values (9)	2167	24.7%

Dash Punctuation

Value	Count	Frequency (%)
-	708	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8758	92.5%
Common	708	7.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	1004	11.5%
n	842	9.6%
e	827	9.4%
a	662	7.6%
r	636	7.3%
l	534	6.1%
o	534	6.1%
h	530	6.1%
t	528	6.0%
d	494	5.6%
Other values (9)	2167	24.7%

Common

Value	Count	Frequency (%)
-	708	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9466	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	1004	10.6%
n	842	8.9%
e	827	8.7%
-	708	7.5%
a	662	7.0%
r	636	6.7%
l	534	5.6%
o	534	5.6%
h	530	5.6%
t	528	5.6%
Other values (10)	2661	28.1%

capital-gains
Real number (ℝ)

Distinct	338
Distinct (%)	33.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25126.1

Minimum	0
Maximum	100500
Zeros	508
Zeros (%)	50.8%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	51025
95-th percentile	70615
Maximum	100500
Range	100500
Interquartile range (IQR)	51025

Descriptive statistics

Standard deviation	27872.188
Coefficient of variation (CV)	1.1092922
Kurtosis	-1.2767035
Mean	25126.1
Median Absolute Deviation (MAD)	0
Skewness	0.47885023
Sum	25126100
Variance	7.7685885 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	508	50.8%
46300	5	0.5%
51500	4	0.4%
68500	4	0.4%
55600	3	0.3%
49700	3	0.3%
51700	3	0.3%
56700	3	0.3%
47600	3	0.3%
44000	3	0.3%
Other values (328)	461	46.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	508	50.8%
800	1	0.1%
10000	1	0.1%
11000	1	0.1%
12100	1	0.1%
12800	1	0.1%
13100	1	0.1%
14100	1	0.1%
16100	1	0.1%
17300	1	0.1%

Value	Count	Frequency (%)
100500	1	0.1%
98800	1	0.1%
94800	1	0.1%
91900	1	0.1%
90700	1	0.1%
88800	1	0.1%
88400	1	0.1%
87800	1	0.1%
84900	1	0.1%
83900	1	0.1%

capital-loss
Real number (ℝ)

Distinct	354
Distinct (%)	35.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-26793.7

Minimum	-111100
Maximum	0
Zeros	475
Zeros (%)	47.5%
Negative	525
Negative (%)	52.5%
Memory size	7.9 KiB

Quantile statistics

Minimum	-111100
5-th percentile	-72305
Q1	-51500
median	-23250
Q3	0
95-th percentile	0
Maximum	0
Range	111100
Interquartile range (IQR)	51500

Descriptive statistics

Standard deviation	28104.097
Coefficient of variation (CV)	-1.0489069
Kurtosis	-1.3138745
Mean	-26793.7
Median Absolute Deviation (MAD)	23250
Skewness	-0.39147194
Sum	-26793700
Variance	7.8984025 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	475	47.5%
-31700	5	0.5%
-53700	5	0.5%
-50300	5	0.5%
-45300	4	0.4%
-51000	4	0.4%
-32800	4	0.4%
-53800	4	0.4%
-49200	4	0.4%
-31400	4	0.4%
Other values (344)	486	48.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-111100	1	0.1%
-93600	1	0.1%
-91400	1	0.1%
-91200	1	0.1%
-90600	1	0.1%
-90200	1	0.1%
-90100	1	0.1%
-89400	1	0.1%
-88300	1	0.1%
-87300	1	0.1%

Value	Count	Frequency (%)
0	475	47.5%
-5700	1	0.1%
-6300	1	0.1%
-8500	1	0.1%
-10600	1	0.1%
-12100	1	0.1%
-13200	1	0.1%
-13800	1	0.1%
-15600	1	0.1%
-15700	2	0.2%

incident_type
Categorical

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Multi-vehicle Collision	419
Single Vehicle Collision	403
Vehicle Theft	94
Parked Car	84

Length

Max length	24
Median length	23
Mean length	21.371
Min length	10

Characters and Unicode

Total characters	21371
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Single Vehicle Collision
2nd row	Vehicle Theft
3rd row	Multi-vehicle Collision
4th row	Single Vehicle Collision
5th row	Vehicle Theft

Common Values

Value	Count	Frequency (%)
Multi-vehicle Collision	419	41.9%
Single Vehicle Collision	403	40.3%
Vehicle Theft	94	9.4%
Parked Car	84	8.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
collision	822	34.2%
vehicle	497	20.7%
multi-vehicle	419	17.4%
single	403	16.8%
theft	94	3.9%
parked	84	3.5%
car	84	3.5%

Most occurring characters

Value	Count	Frequency (%)
l	3382	15.8%
i	3382	15.8%
e	2413	11.3%
o	1644	7.7%
	1403	6.6%
n	1225	5.7%
h	1010	4.7%
c	916	4.3%
C	906	4.2%
s	822	3.8%
Other values (15)	4268	20.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	17146	80.2%
Uppercase Letter	2403	11.2%
Space Separator	1403	6.6%
Dash Punctuation	419	2.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	3382	19.7%
i	3382	19.7%
e	2413	14.1%
o	1644	9.6%
n	1225	7.1%
h	1010	5.9%
c	916	5.3%
s	822	4.8%
t	513	3.0%
u	419	2.4%
Other values (7)	1420	8.3%

Uppercase Letter

Value	Count	Frequency (%)
C	906	37.7%
V	497	20.7%
M	419	17.4%
S	403	16.8%
T	94	3.9%
P	84	3.5%

Space Separator

Value	Count	Frequency (%)
	1403	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	419	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	19549	91.5%
Common	1822	8.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	3382	17.3%
i	3382	17.3%
e	2413	12.3%
o	1644	8.4%
n	1225	6.3%
h	1010	5.2%
c	916	4.7%
C	906	4.6%
s	822	4.2%
t	513	2.6%
Other values (13)	3336	17.1%

Common

Value	Count	Frequency (%)
	1403	77.0%
-	419	23.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	21371	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	3382	15.8%
i	3382	15.8%
e	2413	11.3%
o	1644	7.7%
	1403	6.6%
n	1225	5.7%
h	1010	4.7%
c	916	4.3%
C	906	4.2%
s	822	3.8%
Other values (15)	4268	20.0%

collision_type
Categorical

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Rear Collision	292
Side Collision	276
Front Collision	254
Not Known	178

Length

Max length	15
Median length	14
Mean length	13.364
Min length	9

Characters and Unicode

Total characters	13364
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Side Collision
2nd row	Not Known
3rd row	Rear Collision
4th row	Front Collision
5th row	Not Known

Common Values

Value	Count	Frequency (%)
Rear Collision	292	29.2%
Side Collision	276	27.6%
Front Collision	254	25.4%
Not Known	178	17.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
collision	822	41.1%
rear	292	14.6%
side	276	13.8%
front	254	12.7%
not	178	8.9%
known	178	8.9%

Most occurring characters

Value	Count	Frequency (%)
o	2254	16.9%
i	1920	14.4%
l	1644	12.3%
n	1432	10.7%
	1000	7.5%
s	822	6.2%
C	822	6.2%
e	568	4.3%
r	546	4.1%
t	432	3.2%
Other values (8)	1924	14.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10364	77.6%
Uppercase Letter	2000	15.0%
Space Separator	1000	7.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	2254	21.7%
i	1920	18.5%
l	1644	15.9%
n	1432	13.8%
s	822	7.9%
e	568	5.5%
r	546	5.3%
t	432	4.2%
a	292	2.8%
d	276	2.7%

Uppercase Letter

Value	Count	Frequency (%)
C	822	41.1%
R	292	14.6%
S	276	13.8%
F	254	12.7%
N	178	8.9%
K	178	8.9%

Space Separator

Value	Count	Frequency (%)
	1000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12364	92.5%
Common	1000	7.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	2254	18.2%
i	1920	15.5%
l	1644	13.3%
n	1432	11.6%
s	822	6.6%
C	822	6.6%
e	568	4.6%
r	546	4.4%
t	432	3.5%
R	292	2.4%
Other values (7)	1632	13.2%

Common

Value	Count	Frequency (%)
	1000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	13364	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	2254	16.9%
i	1920	14.4%
l	1644	12.3%
n	1432	10.7%
	1000	7.5%
s	822	6.2%
C	822	6.2%
e	568	4.3%
r	546	4.1%
t	432	3.2%
Other values (8)	1924	14.4%

incident_severity
Categorical

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Minor Damage	354
Total Loss	280
Major Damage	276
Trivial Damage	90

Length

Max length	14
Median length	12
Mean length	11.62
Min length	10

Characters and Unicode

Total characters	11620
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Major Damage
2nd row	Minor Damage
3rd row	Minor Damage
4th row	Major Damage
5th row	Minor Damage

Common Values

Value	Count	Frequency (%)
Minor Damage	354	35.4%
Total Loss	280	28.0%
Major Damage	276	27.6%
Trivial Damage	90	9.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
damage	720	36.0%
minor	354	17.7%
total	280	14.0%
loss	280	14.0%
major	276	13.8%
trivial	90	4.5%

Most occurring characters

Value	Count	Frequency (%)
a	2086	18.0%
o	1190	10.2%
	1000	8.6%
g	720	6.2%
m	720	6.2%
e	720	6.2%
r	720	6.2%
D	720	6.2%
M	630	5.4%
s	560	4.8%
Other values (8)	2554	22.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8620	74.2%
Uppercase Letter	2000	17.2%
Space Separator	1000	8.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	2086	24.2%
o	1190	13.8%
g	720	8.4%
m	720	8.4%
e	720	8.4%
r	720	8.4%
s	560	6.5%
i	534	6.2%
l	370	4.3%
n	354	4.1%
Other values (3)	646	7.5%

Uppercase Letter

Value	Count	Frequency (%)
D	720	36.0%
M	630	31.5%
T	370	18.5%
L	280	14.0%

Space Separator

Value	Count	Frequency (%)
	1000	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10620	91.4%
Common	1000	8.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	2086	19.6%
o	1190	11.2%
g	720	6.8%
m	720	6.8%
e	720	6.8%
r	720	6.8%
D	720	6.8%
M	630	5.9%
s	560	5.3%
i	534	5.0%
Other values (7)	2020	19.0%

Common

Value	Count	Frequency (%)
	1000	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11620	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	2086	18.0%
o	1190	10.2%
	1000	8.6%
g	720	6.2%
m	720	6.2%
e	720	6.2%
r	720	6.2%
D	720	6.2%
M	630	5.4%
s	560	4.8%
Other values (8)	2554	22.0%

authorities_contacted
Categorical

Distinct	5
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Police	292
Fire	223
Other	198
Ambulance	196
None	91

Length

Max length	9
Median length	6
Mean length	5.762
Min length	4

Characters and Unicode

Total characters	5762
Distinct characters	18
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Police
2nd row	Police
3rd row	Police
4th row	Police
5th row	None

Common Values

Value	Count	Frequency (%)
Police	292	29.2%
Fire	223	22.3%
Other	198	19.8%
Ambulance	196	19.6%
None	91	9.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
police	292	29.2%
fire	223	22.3%
other	198	19.8%
ambulance	196	19.6%
none	91	9.1%

Most occurring characters

Value	Count	Frequency (%)
e	1000	17.4%
i	515	8.9%
l	488	8.5%
c	488	8.5%
r	421	7.3%
o	383	6.6%
P	292	5.1%
n	287	5.0%
F	223	3.9%
h	198	3.4%
Other values (8)	1467	25.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4762	82.6%
Uppercase Letter	1000	17.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1000	21.0%
i	515	10.8%
l	488	10.2%
c	488	10.2%
r	421	8.8%
o	383	8.0%
n	287	6.0%
h	198	4.2%
t	198	4.2%
m	196	4.1%
Other values (3)	588	12.3%

Uppercase Letter

Value	Count	Frequency (%)
P	292	29.2%
F	223	22.3%
O	198	19.8%
A	196	19.6%
N	91	9.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5762	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1000	17.4%
i	515	8.9%
l	488	8.5%
c	488	8.5%
r	421	7.3%
o	383	6.6%
P	292	5.1%
n	287	5.0%
F	223	3.9%
h	198	3.4%
Other values (8)	1467	25.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5762	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1000	17.4%
i	515	8.9%
l	488	8.5%
c	488	8.5%
r	421	7.3%
o	383	6.6%
P	292	5.1%
n	287	5.0%
F	223	3.9%
h	198	3.4%
Other values (8)	1467	25.5%

incident_state
Categorical

Distinct	7
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

NY	262
SC	248
WV	217
VA	110
NC	110
Other values (2)	53

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	2000
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	SC
2nd row	VA
3rd row	NY
4th row	OH
5th row	NY

Common Values

Value	Count	Frequency (%)
NY	262	26.2%
SC	248	24.8%
WV	217	21.7%
VA	110	11.0%
NC	110	11.0%
PA	30	3.0%
OH	23	2.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
ny	262	26.2%
sc	248	24.8%
wv	217	21.7%
va	110	11.0%
nc	110	11.0%
pa	30	3.0%
oh	23	2.3%

Most occurring characters

Value	Count	Frequency (%)
N	372	18.6%
C	358	17.9%
V	327	16.4%
Y	262	13.1%
S	248	12.4%
W	217	10.8%
A	140	7.0%
P	30	1.5%
O	23	1.1%
H	23	1.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	2000	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	372	18.6%
C	358	17.9%
V	327	16.4%
Y	262	13.1%
S	248	12.4%
W	217	10.8%
A	140	7.0%
P	30	1.5%
O	23	1.1%
H	23	1.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2000	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	372	18.6%
C	358	17.9%
V	327	16.4%
Y	262	13.1%
S	248	12.4%
W	217	10.8%
A	140	7.0%
P	30	1.5%
O	23	1.1%
H	23	1.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	372	18.6%
C	358	17.9%
V	327	16.4%
Y	262	13.1%
S	248	12.4%
W	217	10.8%
A	140	7.0%
P	30	1.5%
O	23	1.1%
H	23	1.1%

incident_hour_of_the_day
Real number (ℝ)

Distinct	24
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.644

Minimum	0
Maximum	23
Zeros	52
Zeros (%)	5.2%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	6
median	12
Q3	17
95-th percentile	23
Maximum	23
Range	23
Interquartile range (IQR)	11

Descriptive statistics

Standard deviation	6.9513729
Coefficient of variation (CV)	0.59699184
Kurtosis	-1.1929402
Mean	11.644
Median Absolute Deviation (MAD)	6
Skewness	-0.035584466
Sum	11644
Variance	48.321586
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
17	54	5.4%
3	53	5.3%
0	52	5.2%
23	51	5.1%
16	49	4.9%
13	46	4.6%
10	46	4.6%
4	46	4.6%
6	44	4.4%
9	43	4.3%
Other values (14)	516	51.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	52	5.2%
1	29	2.9%
2	31	3.1%
3	53	5.3%
4	46	4.6%
5	33	3.3%
6	44	4.4%
7	40	4.0%
8	36	3.6%
9	43	4.3%

Value	Count	Frequency (%)
23	51	5.1%
22	38	3.8%
21	42	4.2%
20	34	3.4%
19	40	4.0%
18	41	4.1%
17	54	5.4%
16	49	4.9%
15	39	3.9%
14	43	4.3%

number_of_vehicles_involved
Categorical

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

1	581
3	358
4	31
2	30

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	3
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	581	58.1%
3	358	35.8%
4	31	3.1%
2	30	3.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	581	58.1%
3	358	35.8%
4	31	3.1%
2	30	3.0%

Most occurring characters

Value	Count	Frequency (%)
1	581	58.1%
3	358	35.8%
4	31	3.1%
2	30	3.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	581	58.1%
3	358	35.8%
4	31	3.1%
2	30	3.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	581	58.1%
3	358	35.8%
4	31	3.1%
2	30	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	581	58.1%
3	358	35.8%
4	31	3.1%
2	30	3.0%

property_damage
Categorical

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Not Known	360
NO	338
YES	302

Length

Max length	9
Median length	3
Mean length	4.822
Min length	2

Characters and Unicode

Total characters	4822
Distinct characters	11
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	YES
2nd row	Not Known
3rd row	NO
4th row	Not Known
5th row	NO

Common Values

Value	Count	Frequency (%)
Not Known	360	36.0%
NO	338	33.8%
YES	302	30.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
not	360	26.5%
known	360	26.5%
no	338	24.9%
yes	302	22.2%

Most occurring characters

Value	Count	Frequency (%)
o	720	14.9%
n	720	14.9%
N	698	14.5%
t	360	7.5%
	360	7.5%
K	360	7.5%
w	360	7.5%
O	338	7.0%
Y	302	6.3%
E	302	6.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	2302	47.7%
Lowercase Letter	2160	44.8%
Space Separator	360	7.5%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	698	30.3%
K	360	15.6%
O	338	14.7%
Y	302	13.1%
E	302	13.1%
S	302	13.1%

Lowercase Letter

Value	Count	Frequency (%)
o	720	33.3%
n	720	33.3%
t	360	16.7%
w	360	16.7%

Space Separator

Value	Count	Frequency (%)
	360	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4462	92.5%
Common	360	7.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	720	16.1%
n	720	16.1%
N	698	15.6%
t	360	8.1%
K	360	8.1%
w	360	8.1%
O	338	7.6%
Y	302	6.8%
E	302	6.8%
S	302	6.8%

Common

Value	Count	Frequency (%)
	360	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4822	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	720	14.9%
n	720	14.9%
N	698	14.5%
t	360	7.5%
	360	7.5%
K	360	7.5%
w	360	7.5%
O	338	7.0%
Y	302	6.3%
E	302	6.3%

bodily_injuries
Categorical

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

0	340
2	332
1	328

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	2
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	340	34.0%
2	332	33.2%
1	328	32.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	340	34.0%
2	332	33.2%
1	328	32.8%

Most occurring characters

Value	Count	Frequency (%)
0	340	34.0%
2	332	33.2%
1	328	32.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	340	34.0%
2	332	33.2%
1	328	32.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	340	34.0%
2	332	33.2%
1	328	32.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	340	34.0%
2	332	33.2%
1	328	32.8%

witnesses
Categorical

Distinct	4
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

1	258
2	250
0	249
3	243

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	1000
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	0
3rd row	3
4th row	2
5th row	1

Common Values

Value	Count	Frequency (%)
1	258	25.8%
2	250	25.0%
0	249	24.9%
3	243	24.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	258	25.8%
2	250	25.0%
0	249	24.9%
3	243	24.3%

Most occurring characters

Value	Count	Frequency (%)
1	258	25.8%
2	250	25.0%
0	249	24.9%
3	243	24.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	258	25.8%
2	250	25.0%
0	249	24.9%
3	243	24.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	1000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	258	25.8%
2	250	25.0%
0	249	24.9%
3	243	24.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	258	25.8%
2	250	25.0%
0	249	24.9%
3	243	24.3%

police_report_available
Categorical

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Not Known	343
NO	343
YES	314

Length

Max length	9
Median length	3
Mean length	4.715
Min length	2

Characters and Unicode

Total characters	4715
Distinct characters	11
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	YES
2nd row	Not Known
3rd row	NO
4th row	NO
5th row	NO

Common Values

Value	Count	Frequency (%)
Not Known	343	34.3%
NO	343	34.3%
YES	314	31.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
not	343	25.5%
known	343	25.5%
no	343	25.5%
yes	314	23.4%

Most occurring characters

Value	Count	Frequency (%)
N	686	14.5%
o	686	14.5%
n	686	14.5%
t	343	7.3%
	343	7.3%
K	343	7.3%
w	343	7.3%
O	343	7.3%
Y	314	6.7%
E	314	6.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	2314	49.1%
Lowercase Letter	2058	43.6%
Space Separator	343	7.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	686	29.6%
K	343	14.8%
O	343	14.8%
Y	314	13.6%
E	314	13.6%
S	314	13.6%

Lowercase Letter

Value	Count	Frequency (%)
o	686	33.3%
n	686	33.3%
t	343	16.7%
w	343	16.7%

Space Separator

Value	Count	Frequency (%)
	343	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4372	92.7%
Common	343	7.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	686	15.7%
o	686	15.7%
n	686	15.7%
t	343	7.8%
K	343	7.8%
w	343	7.8%
O	343	7.8%
Y	314	7.2%
E	314	7.2%
S	314	7.2%

Common

Value	Count	Frequency (%)
	343	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4715	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	686	14.5%
o	686	14.5%
n	686	14.5%
t	343	7.3%
	343	7.3%
K	343	7.3%
w	343	7.3%
O	343	7.3%
Y	314	6.7%
E	314	6.7%

total_claim_amount
Real number (ℝ)

Distinct	763
Distinct (%)	76.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	52761.94

Minimum	100
Maximum	114920
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	100
5-th percentile	4320
Q1	41812.5
median	58055
Q3	70592.5
95-th percentile	88413
Maximum	114920
Range	114820
Interquartile range (IQR)	28780

Descriptive statistics

Standard deviation	26401.533
Coefficient of variation (CV)	0.50038974
Kurtosis	-0.45408143
Mean	52761.94
Median Absolute Deviation (MAD)	13855
Skewness	-0.59458199
Sum	52761940
Variance	6.9704095 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
59400	5	0.5%
2640	4	0.4%
70400	4	0.4%
4320	4	0.4%
44200	4	0.4%
75400	4	0.4%
60600	4	0.4%
3190	4	0.4%
58500	4	0.4%
70290	4	0.4%
Other values (753)	959	95.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
100	1	0.1%
1920	1	0.1%
2160	1	0.1%
2250	1	0.1%
2400	1	0.1%
2520	1	0.1%
2640	4	0.4%
2700	2	0.2%
2800	1	0.1%
2860	1	0.1%

Value	Count	Frequency (%)
114920	1	0.1%
112320	1	0.1%
108480	1	0.1%
108030	1	0.1%
107900	1	0.1%
105820	1	0.1%
105040	1	0.1%
104610	1	0.1%
103560	1	0.1%
101860	1	0.1%

injury_claim
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	638
Distinct (%)	63.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7433.42

Minimum	0
Maximum	21450
Zeros	25
Zeros (%)	2.5%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	450
Q1	4295
median	6775
Q3	11305
95-th percentile	15662
Maximum	21450
Range	21450
Interquartile range (IQR)	7010

Descriptive statistics

Standard deviation	4880.9519
Coefficient of variation (CV)	0.65662264
Kurtosis	-0.76308706
Mean	7433.42
Median Absolute Deviation (MAD)	3705
Skewness	0.26481088
Sum	7433420
Variance	23823691
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	25	2.5%
640	7	0.7%
480	7	0.7%
660	5	0.5%
580	5	0.5%
13520	5	0.5%
1180	5	0.5%
860	5	0.5%
6340	5	0.5%
780	5	0.5%
Other values (628)	926	92.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	25	2.5%
10	1	0.1%
220	1	0.1%
250	1	0.1%
280	2	0.2%
290	1	0.1%
300	3	0.3%
330	2	0.2%
350	1	0.1%
360	1	0.1%

Value	Count	Frequency (%)
21450	1	0.1%
21330	1	0.1%
20700	1	0.1%
19020	1	0.1%
18520	1	0.1%
18220	1	0.1%
18180	1	0.1%
18080	1	0.1%
18000	1	0.1%
17880	1	0.1%

property_claim
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	626
Distinct (%)	62.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7399.57

Minimum	0
Maximum	23670
Zeros	19
Zeros (%)	1.9%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	0
5-th percentile	450
Q1	4445
median	6750
Q3	10885
95-th percentile	15540
Maximum	23670
Range	23670
Interquartile range (IQR)	6440

Descriptive statistics

Standard deviation	4824.7262
Coefficient of variation (CV)	0.65202791
Kurtosis	-0.37638631
Mean	7399.57
Median Absolute Deviation (MAD)	3290
Skewness	0.37816878
Sum	7399570
Variance	23277983
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	19	1.9%
860	6	0.6%
480	5	0.5%
660	5	0.5%
10000	5	0.5%
640	5	0.5%
650	5	0.5%
11080	5	0.5%
840	4	0.4%
5310	4	0.4%
Other values (616)	937	93.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	19	1.9%
20	1	0.1%
240	1	0.1%
250	1	0.1%
260	1	0.1%
280	3	0.3%
290	2	0.2%
300	3	0.3%
320	3	0.3%
330	1	0.1%

Value	Count	Frequency (%)
23670	1	0.1%
21810	1	0.1%
21630	1	0.1%
21580	1	0.1%
21240	1	0.1%
20550	1	0.1%
20310	1	0.1%
20280	1	0.1%
19950	1	0.1%
19650	1	0.1%

vehicle_claim
Real number (ℝ)

Distinct	726
Distinct (%)	72.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	37928.95

Minimum	70
Maximum	79560
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	70
5-th percentile	3273.5
Q1	30292.5
median	42100
Q3	50822.5
95-th percentile	63094.5
Maximum	79560
Range	79490
Interquartile range (IQR)	20530

Descriptive statistics

Standard deviation	18886.253
Coefficient of variation (CV)	0.49793767
Kurtosis	-0.44657292
Mean	37928.95
Median Absolute Deviation (MAD)	9840
Skewness	-0.62109793
Sum	37928950
Variance	3.5669055 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5040	7	0.7%
3360	6	0.6%
52080	5	0.5%
4720	5	0.5%
3600	5	0.5%
44800	5	0.5%
33600	5	0.5%
42720	4	0.4%
41580	4	0.4%
35000	4	0.4%
Other values (716)	950	95.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
70	1	0.1%
1440	2	0.2%
1680	2	0.2%
1750	1	0.1%
1760	1	0.1%
1800	1	0.1%
1960	2	0.2%
1980	1	0.1%
2030	1	0.1%
2080	1	0.1%

Value	Count	Frequency (%)
79560	1	0.1%
77760	1	0.1%
77670	2	0.2%
76400	1	0.1%
76000	1	0.1%
75600	1	0.1%
75530	1	0.1%
74790	1	0.1%
73620	1	0.1%
73260	1	0.1%

auto_make
Categorical

Distinct	14
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Saab	80
Dodge	80
Suburu	80
Nissan	78
Chevrolet	76
Other values (9)	606

Length

Max length	10
Median length	9
Mean length	5.703
Min length	3

Characters and Unicode

Total characters	5703
Distinct characters	33
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Saab
2nd row	Mercedes
3rd row	Dodge
4th row	Chevrolet
5th row	Accura

Common Values

Value	Count	Frequency (%)
Saab	80	8.0%
Dodge	80	8.0%
Suburu	80	8.0%
Nissan	78	7.8%
Chevrolet	76	7.6%
Ford	72	7.2%
BMW	72	7.2%
Toyota	70	7.0%
Audi	69	6.9%
Accura	68	6.8%
Other values (4)	255	25.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
saab	80	8.0%
dodge	80	8.0%
suburu	80	8.0%
nissan	78	7.8%
chevrolet	76	7.6%
ford	72	7.2%
bmw	72	7.2%
toyota	70	7.0%
audi	69	6.9%
accura	68	6.8%
Other values (4)	255	25.5%

Most occurring characters

Value	Count	Frequency (%)
e	629	11.0%
a	499	8.7%
o	491	8.6%
u	377	6.6%
r	361	6.3%
d	341	6.0%
s	289	5.1%
c	201	3.5%
n	201	3.5%
S	160	2.8%
Other values (23)	2154	37.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4559	79.9%
Uppercase Letter	1144	20.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	629	13.8%
a	499	10.9%
o	491	10.8%
u	377	8.3%
r	361	7.9%
d	341	7.5%
s	289	6.3%
c	201	4.4%
n	201	4.4%
b	160	3.5%
Other values (10)	1010	22.2%

Uppercase Letter

Value	Count	Frequency (%)
S	160	14.0%
M	137	12.0%
A	137	12.0%
D	80	7.0%
N	78	6.8%
C	76	6.6%
B	72	6.3%
F	72	6.3%
W	72	6.3%
T	70	6.1%
Other values (3)	190	16.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5703	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	629	11.0%
a	499	8.7%
o	491	8.6%
u	377	6.6%
r	361	6.3%
d	341	6.0%
s	289	5.1%
c	201	3.5%
n	201	3.5%
S	160	2.8%
Other values (23)	2154	37.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5703	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	629	11.0%
a	499	8.7%
o	491	8.6%
u	377	6.6%
r	361	6.3%
d	341	6.0%
s	289	5.1%
c	201	3.5%
n	201	3.5%
S	160	2.8%
Other values (23)	2154	37.8%

auto_year
Real number (ℝ)

Distinct	21
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2005.103

Minimum	1995
Maximum	2015
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1995
5-th percentile	1995
Q1	2000
median	2005
Q3	2010
95-th percentile	2014
Maximum	2015
Range	20
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.0158608
Coefficient of variation (CV)	0.0030002752
Kurtosis	-1.1718678
Mean	2005.103
Median Absolute Deviation (MAD)	5
Skewness	-0.048288807
Sum	2005103
Variance	36.190582
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
1995	56	5.6%
1999	55	5.5%
2005	54	5.4%
2006	53	5.3%
2011	53	5.3%
2007	52	5.2%
2003	51	5.1%
2009	50	5.0%
2010	50	5.0%
2013	49	4.9%
Other values (11)	477	47.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1995	56	5.6%
1996	37	3.7%
1997	46	4.6%
1998	40	4.0%
1999	55	5.5%
2000	42	4.2%
2001	42	4.2%
2002	49	4.9%
2003	51	5.1%
2004	39	3.9%

Value	Count	Frequency (%)
2015	47	4.7%
2014	44	4.4%
2013	49	4.9%
2012	46	4.6%
2011	53	5.3%
2010	50	5.0%
2009	50	5.0%
2008	45	4.5%
2007	52	5.2%
2006	53	5.3%

fraud_reported
Boolean

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

False	753
True	247

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	753	75.3%
True	247	24.7%

Auto

The auto setting is an interpretable pairwise column metric of the following mapping:

Variable_type-Variable_type : Method, Range
Categorical-Categorical : Cramer's V, [0,1]
Numerical-Categorical : Cramer's V, [0,1] (using a discretized numerical column)
Numerical-Numerical : Spearman's ρ, [-1,1]

The number of bins used in the discretization for the Numerical-Categorical column pair can be changed using config.correlations["auto"].n_bins. The number of bins affects the granularity of the association you wish to measure.

This configuration uses the recommended metric for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	months_as_customer	age	policy_state	policy_deductable	policy_annual_premium	umbrella_limit	insured_zip	insured_sex	insured_education_level	insured_occupation	insured_relationship	capital-gains	capital-loss	incident_type	collision_type	incident_severity	authorities_contacted	incident_state	incident_hour_of_the_day	number_of_vehicles_involved	property_damage	bodily_injuries	witnesses	police_report_available	total_claim_amount	injury_claim	property_claim	vehicle_claim	auto_make	auto_year	fraud_reported
0	328	48	OH	1000	1406.91	0	466132	MALE	MD	craft-repair	husband	53300	0	Single Vehicle Collision	Side Collision	Major Damage	Police	SC	5	1	YES	1	2	YES	71610	6510	13020	52080	Saab	2004	Y
1	228	42	IN	2000	1197.22	5000000	468176	MALE	MD	machine-op-inspct	other-relative	0	0	Vehicle Theft	Not Known	Minor Damage	Police	VA	8	1	Not Known	0	0	Not Known	5070	780	780	3510	Mercedes	2007	Y
2	134	29	OH	2000	1413.14	5000000	430632	FEMALE	PhD	sales	own-child	35100	0	Multi-vehicle Collision	Rear Collision	Minor Damage	Police	NY	7	3	NO	2	3	NO	34650	7700	3850	23100	Dodge	2007	N
3	256	41	IL	2000	1415.74	6000000	608117	FEMALE	PhD	armed-forces	unmarried	48900	-62400	Single Vehicle Collision	Front Collision	Major Damage	Police	OH	5	1	Not Known	1	2	NO	63400	6340	6340	50720	Chevrolet	2014	Y
4	228	44	IL	1000	1583.91	6000000	610706	MALE	Associate	sales	unmarried	66000	-46000	Vehicle Theft	Not Known	Minor Damage	None	NY	20	1	NO	0	1	NO	6500	1300	650	4550	Accura	2009	N
5	256	39	OH	1000	1351.10	0	478456	FEMALE	PhD	tech-support	unmarried	0	0	Multi-vehicle Collision	Rear Collision	Major Damage	Fire	SC	19	3	NO	0	2	NO	64100	6410	6410	51280	Saab	2003	Y
6	137	34	IN	1000	1333.35	0	441716	MALE	PhD	prof-specialty	husband	0	-77000	Multi-vehicle Collision	Front Collision	Minor Damage	Police	NY	0	3	Not Known	0	0	Not Known	78650	21450	7150	50050	Nissan	2012	N
7	165	37	IL	1000	1137.03	0	603195	MALE	Associate	tech-support	unmarried	0	0	Multi-vehicle Collision	Front Collision	Total Loss	Police	VA	23	3	Not Known	2	2	YES	51590	9380	9380	32830	Audi	2015	N
8	27	33	IL	500	1442.99	0	601734	FEMALE	PhD	other-service	own-child	0	0	Single Vehicle Collision	Front Collision	Total Loss	Police	WV	21	1	NO	1	1	YES	27700	2770	2770	22160	Toyota	2012	N
9	212	42	IL	500	1315.68	0	600983	MALE	PhD	priv-house-serv	wife	0	-39300	Single Vehicle Collision	Rear Collision	Total Loss	Other	NC	14	1	NO	2	1	Not Known	42300	4700	4700	32900	Saab	1996	N

	months_as_customer	age	policy_state	policy_deductable	policy_annual_premium	umbrella_limit	insured_zip	insured_sex	insured_education_level	insured_occupation	insured_relationship	capital-gains	capital-loss	incident_type	collision_type	incident_severity	authorities_contacted	incident_state	incident_hour_of_the_day	number_of_vehicles_involved	property_damage	bodily_injuries	witnesses	police_report_available	total_claim_amount	injury_claim	property_claim	vehicle_claim	auto_make	auto_year	fraud_reported
990	286	43	IL	500	1564.43	3000000	477644	FEMALE	MD	prof-specialty	unmarried	77500	-32800	Single Vehicle Collision	Rear Collision	Minor Damage	Fire	NY	18	1	Not Known	2	2	YES	34290	3810	3810	26670	Jeep	2013	N
991	257	44	OH	1000	1280.88	0	433981	MALE	MD	other-service	other-relative	59400	-32200	Single Vehicle Collision	Rear Collision	Total Loss	Other	WV	21	1	NO	0	1	NO	46980	0	5220	41760	Accura	2002	N
992	94	26	IN	500	722.66	0	433696	MALE	MD	exec-managerial	husband	50300	0	Multi-vehicle Collision	Front Collision	Major Damage	Fire	OH	6	3	YES	1	2	YES	36700	3670	7340	25690	Nissan	2010	N
993	124	28	OH	1000	1235.14	0	443567	MALE	MD	exec-managerial	husband	0	-32100	Multi-vehicle Collision	Side Collision	Total Loss	Other	OH	20	3	Not Known	0	1	Not Known	60200	6020	6020	48160	Volkswagen	2012	N
994	141	30	IN	1000	1347.04	0	430665	MALE	High School	sales	own-child	0	-82100	Parked Car	Not Known	Minor Damage	None	SC	6	1	Not Known	1	2	YES	6480	540	1080	4860	Honda	1996	N
995	3	38	OH	1000	1310.80	0	431289	FEMALE	Masters	craft-repair	unmarried	0	0	Single Vehicle Collision	Front Collision	Minor Damage	Fire	NC	20	1	YES	0	1	Not Known	87200	17440	8720	61040	Honda	2006	N
996	285	41	IL	1000	1436.79	0	608177	FEMALE	PhD	prof-specialty	wife	70900	0	Single Vehicle Collision	Rear Collision	Major Damage	Fire	SC	23	1	YES	2	3	Not Known	108480	18080	18080	72320	Volkswagen	2015	N
997	130	34	OH	500	1383.49	3000000	442797	FEMALE	Masters	armed-forces	other-relative	35100	0	Multi-vehicle Collision	Side Collision	Minor Damage	Police	NC	4	3	Not Known	2	3	YES	67500	7500	7500	52500	Suburu	1996	N
998	458	62	IL	2000	1356.92	5000000	441714	MALE	Associate	handlers-cleaners	wife	0	0	Single Vehicle Collision	Rear Collision	Major Damage	Other	NY	2	1	Not Known	0	1	YES	46980	5220	5220	36540	Audi	1998	N
999	456	60	OH	1000	766.19	0	612260	FEMALE	Associate	sales	husband	0	0	Parked Car	Not Known	Minor Damage	Police	WV	6	1	Not Known	0	3	Not Known	5060	460	920	3680	Mercedes	2007	N

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Dash Punctuation

Most occurring scripts